Search results for: interactive architecture
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2616

Search results for: interactive architecture

96 Anti-Graft Instruments and Their Role in Curbing Corruption: Integrity Pact and Its Impact on Indian Procurement

Authors: Jot Prakash Kaur

Abstract:

The paper aims to showcase that with the introduction of anti-graft instruments and willingness of the governments towards their implementation, a significant change can be witnessed in the anti-corruption landscape of any country. Since the past decade anti-graft instruments have been introduced by several international non-governmental organizations with the vision of curbing corruption. Transparency International’s ‘Integrity Pact’ has been one such initiative. Integrity Pact has been described as a tool for preventing corruption in public contracting. Integrity Pact has found its relevance in a developing country like India where public procurement constitutes 25-30 percent of Gross Domestic Product. Corruption in public procurement has been a cause of concern even though India has in place a whole architecture of rules and regulations governing public procurement. Integrity Pact was first adopted by a leading Oil and Gas government company in 2006. Till May 2015, over ninety organizations had adopted Integrity Pact, of which majority of them are central government units. The methodology undertaken to understand impact of Integrity Pact on Public procurement is through analyzing information received from important stakeholders of the instrument. Government, information was sought through Right to Information Act 2005 about the details of adoption of this instrument by various government organizations and departments. Contractor, Company websites and annual reports were used to find out the steps taken towards implementation of Integrity Pact. Civil Society, Transparency International India’s resource materials which include publications and reports on Integrity Pact were also used to understand the impact of Integrity Pact. Some of the findings of the study include organizations adopting Integrity pacts in all kinds of contracts such that 90% of their procurements fall under Integrity Pact. Indian State governments have found merit in Integrity Pact and have adopted it in their procurement contracts. Integrity Pact has been instrumental in creating a brand image of companies. External Monitors, an essential feature of Integrity Pact have emerged as arbitrators for the bidders and are the first line of procurement auditors for the organizations. India has cancelled two defense contracts finding it conflicting with the provisions of Integrity Pact. Some of the clauses of Integrity Pact have been included in the proposed Public Procurement legislation. Integrity Pact has slowly but steadily grown to become an integral part of big ticket procurement in India. Government’s commitment to implement Integrity Pact has changed the way in which public procurement is conducted in India. Public Procurement was a segment infested with corruption but with the adoption of Integrity Pact a number of clean up acts have been performed to make procurement transparent. The paper is divided in five sections. First section elaborates on Integrity Pact. Second section talks about stakeholders of the instrument and the role it plays in its implementation. Third section talks about the efforts taken by the government to implement Integrity Pact in India. Fourth section talks about the role of External Monitor as Arbitrator. The final section puts forth suggestions to strengthen the existing form of Integrity Pact and increase its reach.

Keywords: corruption, integrity pact, procurement, vigilance

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95 A Generalized Framework for Adaptive Machine Learning Deployments in Algorithmic Trading

Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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94 Influence of Dietary Boron on Gut Absorption of Nutrients, Blood Metabolites and Tissue Pathology

Authors: T. Vijay Bhasker, N. K. S Gowda, P. Krishnamoorthy, D. T. Pal, A. K. Pattanaik, A. K. Verma

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Boron (B) is a newer trace element and its biological importance and dietary essentiality is unclear in animals. The available literature suggests its putative role in bone mineralization, antioxidant status and steroid hormone synthesis. A feeding trial was conducted in Wister strain (Rattus norvegicus) albino rats for duration of 90 days. A total of 84 healthy weaned (3-4 weeks) experimental rats were randomly divided into 7 dietary groups (4 replicates of three each) viz., A (Basal diet/ Control), B (Basal diet + 5 ppm B), C (Basal diet + 10 ppm B), D (Basal diet + 20 ppm B), E (Basal diet + 40 ppm B), F (Basal diet-Ca 50%), G (Basal diet-Ca 50% + 40 ppm B). Dietary level of calcium (Ca) was maintained at two levels, 100% and 50% of requirement. Sodium borate was used as source of boron along with other ingredients of basal diet while preparing the pelletized diets. All the rats were kept in proper ventilated laboratory animal house maintained at temperature (23±2º C) and humidity (50 to 70%). At the end of experiment digestibility trial was conducted for 5 days to estimate nutrient digestibility and gut absorption of minerals. Eight rats from each group were sacrificed to collect the vital organs (liver, kidney and spleen) to study histopathology. Blood sample was drawn by heart puncture to determine biochemical profile. The average daily feed intake (g/rat/day), water intake (ml/rat/day) and body weight gain (g/rat/day) were similar among the dietary groups. The digestibility (%) of organic matter and crude fat were significantly improved (P < 0.05) was by B supplementation. The gut absorption (%) Ca was significantly increased (P < 0.01) in B supplemented groups compared to control. However, digestibility of dry matter and crude protein, gut absorption of magnesium and phosphorus showed a non-significant increasing trend with B supplementation. The gut absorption (%) of B (P < 0.01) was significantly lowered (P<0.05) in supplemented groups compared to un-supplemented ones. The serum level of triglycerides (mg/dL), HDL-cholesterol (mg/dL) and alanine transaminase (IU/L) were significantly lowered (P < 0.05) in B supplemented groups. While serum level of glucose (mg/dL) and alkaline phosphatase (KA units) showed a non-significant decreasing trend with B supplementation. However the serum levels of total cholesterol (mg/dL) and aspartate transaminase (IU/L) were similar among dietary groups. The histology sections of kidney and spleen revealed no significant changes among the dietary groups and were observed to be normal in anatomical architecture. However, the liver histology revealed cell degenerative changes with vacuolar degeneration and nuclear condensation in Ca deficient groups. But the comparative degenerative changes were mild in 40 ppm B supplemented Ca deficient group. In conclusion, dietary supplementation of graded levels of boron in rats had a positive effect on metabolism and health by improving nutrient digestibility and gut absorption of Ca. This indicates the beneficial role of dietary boron supplementation.

Keywords: boron, calcium, nutrient utilization, histopathology

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93 Identification of Three Strategies to Enhance University Students’ Professional Identity, Using Hierarchical Regression Analysis

Authors: Alba Barbara-i-Molinero, Rosalia Cascon-Pereira, Ana Beatriz Hernandez

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Students’ transitions from high school to the university have been challenged by the lack of continuity between both contexts. This mismatch directly affects students by generating feelings of anxiety and uncertainty, which increases the dropout rates and reduces students’ academic success. This discontinuity emanates because ‘transitions concern a restructuring of what the person does and who the person perceives him or herself to be’. Hence, identity becomes essential in these transitions. Generally, identity is the answer to questions such as who am I? or who are we? This is integrated by personal identity, and as many social identities as groups, the individual feels he/she is a part. A case in point to construct a social identity is the identification with a profession. For this reason, a way to lighten the generated tension during transitions is applying strategies orientated to enhance students’ professional identity in their point of entry to the higher education institution. That would create a sense of continuity between high school and higher education contexts, increasing their Professional Identity Strength. To develop the strategies oriented to enhance students Professional Identity, it is important to analyze what influences it. There exist several influencing factors that influence Professional Identity (e.g., professional status, the recommendation of family and peers, the academic environment, or the chosen bachelor degree). There is a gap in the literature analyzing the impact of these factors on more than one bachelor degree. In this regards, our study takes an additional step with the aim of evaluating the influence of several factors on Professional Identity using a cohort of university students from multiple degrees between the ages of 17-19 years. To do so, we used hierarchical regression analyses to assess the impact of the following factors: External Motivation Conditionals (EMC), Educational Experience Conditionals (EEC) and Personal Motivational Conditional (PMP). After conducting the analyses, we found that the assessed factors influenced students’ professional identity differently according to their bachelor degree and discipline. For example, PMC and EMC positively affected science students, while architecture, law and economics and engineering students were just influenced by PMC. Basing on that influences, we proposed three different strategies aimed to enhance students’ professional identity, in the short and long term. These strategies are: to enhance students’ professional identity before the incorporation to university through campuses and icebreaker activities; to apply recruitment strategies aimed to provide realistic information of the bachelor degree; and to incorporate different activities, such as in-vitro, in situ and self-directed activities aimed to enhance longitudinally students’ professional identity from the university. From these results, theoretical contributions and practical implications arise. First, we contribute to the literature by identifying which factors influence students from different bachelor degrees since there is still no evidence. And, second, using as a benchmark the obtained results, we contribute from a practical perspective, by proposing several alternative strategies to increase students’ professional identity strength aiming to lighten their transition from high school to higher education.

Keywords: professional identity, higher education, educational strategies , students

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92 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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91 Modeling the International Economic Relations Development: The Prospects for Regional and Global Economic Integration

Authors: M. G. Shilina

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The interstate economic interaction phenomenon is complex. ‘Economic integration’, as one of its types, can be explored through the prism of international law, the theories of the world economy, politics and international relations. The most objective study of the phenomenon requires a comprehensive multifactoral approach. In new geopolitical realities, the problems of coexistence and possible interconnection of various mechanisms of interstate economic interaction are actively discussed. Currently, the Eurasian continent states support the direction to economic integration. At the same time, the existing international economic law fragmentation in Eurasia is seen as the important problem. The Eurasian space is characterized by a various types of interstate relations: international agreements (multilateral and bilateral), and a large number of cooperation formats (from discussion platforms to organizations aimed at deep integration). For their harmonization, it is necessary to have a clear vision to the phased international economic relations regulation options. In the conditions of rapid development of international economic relations, the modeling (including prognostic) can be optimally used as the main scientific method for presenting the phenomenon. On the basis of this method, it is possible to form the current situation vision and the best options for further action. In order to determine the most objective version of the integration development, the combination of several approaches were used. The normative legal approach- the descriptive method of legal modeling- was taken as the basis for the analysis. A set of legal methods was supplemented by the international relations science prognostic methods. The key elements of the model are the international economic organizations and states' associations existing in the Eurasian space (the Eurasian Economic Union (EAEU), the European Union (EU), the Shanghai Cooperation Organization (SCO), Chinese project ‘One belt-one road’ (OBOR), the Commonwealth of Independent States (CIS), BRICS, etc.). A general term for the elements of the model is proposed - the interstate interaction mechanisms (IIM). The aim of building a model of current and future Eurasian economic integration is to show optimal options for joint economic development of the states and IIMs. The long-term goal of this development is the new economic and political space, so-called the ‘Great Eurasian Community’. The process of achievement this long-term goal consists of successive steps. Modeling the integration architecture and dividing the interaction into stages led us to the following conclusion: the SCO is able to transform Eurasia into a single economic space. Gradual implementation of the complex phased model, in which the SCO+ plays a key role, will allow building an effective economic integration for all its participants, to create an economically strong community. The model can have practical value for politicians, lawyers, economists and other participants involved in the economic integration process. A clear, systematic structure can serve as a basis for further governmental action.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, The Silk Road Economic Belt

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90 The Effect of Calcium Phosphate Composite Scaffolds on the Osteogenic Differentiation of Rabbit Dental Pulp Stem Cells

Authors: Ling-Ling E, Lin Feng, Hong-Chen Liu, Dong-Sheng Wang, Zhanping Shi, Juncheng Wang, Wei Luo, Yan Lv

Abstract:

The objective of this study was to compare the effects of the two calcium phosphate composite scaffolds on the attachment, proliferation and osteogenic differentiation of rabbit dental pulp stem cells (DPSCs). One nano-hydroxyapatite/collagen/poly (L-lactide) (nHAC/PLA), imitating the composition and the micro-structure characteristics of the natural bone, was made by Beijing Allgens Medical Science & Technology Co., Ltd. (China). The other beta-tricalcium phosphate (β-TCP), being fully interoperability globular pore structure, was provided by Shanghai Bio-lu Biomaterials Co, Ltd. (China). We compared the absorption water rate and the protein adsorption rate of two scaffolds and the characterization of DPSCs cultured on the culture plate and both scaffolds under osteogenic differentiation media (ODM) treatment. The constructs were then implanted subcutaneously into the back of severe combined immunodeficient (SCID) mice for 8 and 12 weeks to compare their bone formation capacity. The results showed that the ODM-treated DPSCs expressed osteocalcin (OCN), bone sialoprotein (BSP), type I collagen (COLI) and osteopontin (OPN) by immunofluorescence staining. Positive alkaline phosphatase (ALP) staining, calcium deposition and calcium nodules were also observed on the ODM-treated DPSCs. The nHAC/PLA had significantly higher absorption water rate and protein adsorption rate than ß-TCP. The initial attachment of DPSCs seeded onto nHAC/PLA was significantly higher than that onto ß-TCP; and the proliferation rate of the cells was significantly higher than that of ß-TCP on 1, 3 and 7 days of cell culture. DPSCs+ß-TCP had significantly higher ALP activity, calcium/phosphorus content and mineral formation than DPSCs+nHAC/PLA. When implanted into the back of SCID mice, nHAC/PLA alone had no new bone formation, newly formed mature bone and osteoid were only observed in β-TCP alone, DPSCs+nHAC/PLA and DPSCs+β-TCP, and this three groups displayed increased bone formation over the 12-week period. The percentage of total bone formation area had no difference between DPSCs+β-TCP and DPSCs+nHAC/PLA at each time point,but the percentage of mature bone formation area of DPSCs+β-TCP was significantly higher than that of DPSCs+nHAC/PLA. Our results demonstrated that the DPSCs on nHAC/PLA had a better proliferation and that the DPSCs on β-TCP had a more mineralization in vitro, much more newly formed mature bones in vivo were presented in DPSCs+β-TCP group. These findings have provided a further knowledge that scaffold architecture has a different influence on the attachment, proliferation and differentiation of cells. This study may provide insight into the clinical periodontal bone tissue repair with DPSCs+β-TCP construct.

Keywords: dental pulp stem cells, nano-hydroxyapatite/collagen/poly(L-lactide), beta-tricalcium phosphate, periodontal tissue engineering, bone regeneration

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89 An Improved Approach for Hybrid Rocket Injection System Design

Authors: M. Invigorito, G. Elia, M. Panelli

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Hybrid propulsion combines beneficial properties of both solid and liquid rockets, such as multiple restarts, throttability as well as simplicity and reduced costs. A nitrous oxide (N2O)/paraffin-based hybrid rocket engine demonstrator is currently under development at the Italian Aerospace Research Center (CIRA) within the national research program HYPROB, funded by the Italian Ministry of Research. Nitrous oxide belongs to the class of self-pressurizing propellants that exhibit a high vapor pressure at standard ambient temperature. This peculiar feature makes those fluids very attractive for space rocket applications because it avoids the use of complex pressurization systems, leading to great benefits in terms of weight savings and reliability. To avoid feed-system-coupled instabilities, the phase change is required to occur through the injectors. In this regard, the oxidizer is stored in liquid condition while target chamber pressures are designed to lie below vapor pressure. The consequent cavitation and flash vaporization constitute a remarkably complex phenomenology that arises great modelling challenges. Thus, it is clear that the design of the injection system is fundamental for the full exploitation of hybrid rocket engine throttability. The Analytical Hierarchy Process has been used to select the injection architecture as best compromise among different design criteria such as functionality, technology innovation and cost. The impossibility to use engineering simplified relations for the dimensioning of the injectors led to the needs of applying a numerical approach based on OpenFOAM®. The numerical tool has been validated with selected experimental data from literature. Quantitative, as well as qualitative comparisons are performed in terms of mass flow rate and pressure drop across the injector for several operating conditions. The results show satisfactory agreement with the experimental data. Modeling assumptions, together with their impact on numerical predictions are discussed in the paper. Once assessed the reliability of the numerical tool, the injection plate has been designed and sized to guarantee the required amount of oxidizer in the combustion chamber and therefore to assure high combustion efficiency. To this purpose, the plate has been designed with multiple injectors whose number and diameter have been selected in order to reach the requested mass flow rate for the two operating conditions of maximum and minimum thrust. The overall design has been finally verified through three-dimensional computations in cavitating non-reacting conditions and it has been verified that the proposed design solution is able to guarantee the requested values of mass flow rates.

Keywords: hybrid rocket, injection system design, OpenFOAM®, cavitation

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88 Exposure of Pacu, Piaractus mesopotamicus Gill Tissue to a High Stocking Density: An Ion Regulatory and Microscopy Study

Authors: Wiolene Montanari Nordi, Debora Botequio Moretti, Mariana Caroline Pontin, Jessica Pampolini, Raul Machado-Neto

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Gills are organs responsible for respiration and osmoregulation between the fish internal environment and water. Under stress conditions, oxidative response and gill plasticity to attempt to increase gas exchange area are noteworthy, compromising the physiological processes and therefore fish health. Colostrum is a dietary source of nutrients, immunoglobulin, antioxidant and bioactive molecules, essential for immunological protection and development of the gastrointestinal epithelium. The hypothesis of this work is that antioxidant factors present in the colostrum, unprecedentedly tested in gills, can minimize or reduce the alteration of its epithelium structure of juvenile pacu (Piaractus mesopotamicus) subjected to high stocking density. The histological changes in the gills architecture were characterized by the frequency, incidence and severity of the tissue alteration and ionic status. Juvenile (50 kg fish/m3) were fed with pelleted diets containing 0, 10, 20 or 30% of lyophilized bovine colostrum (LBC) inclusion and at 30 experimental days, gill and blood samples were collected in eight fish per treatment. The study revealed differences in the type, frequency and severity (histological alterations index – HAI) of tissue alterations among the treatments, however, no distinct differences in the incidence of alteration (mean alteration value – MAV) were observed. The main histological changes in gill were elevation of the lamellar epithelium, excessive cell proliferation of the filament and lamellar epithelium causing total or partial melting of the lamella, hyperplasia and hypertrophy of lamellar and filament epithelium, uncontrolled thickening of filament and lamellar tissues, mucous and chloride cells presence in the lamella, aneurysms, vascular congestion and presence of parasites. The MAV obtained per treatment were 2.0, 2.5, 1.8 and 2.5 to fish fed diets containing 0, 10, 20 and 30% of LBC inclusion, respectively, classifying the incidence of gill alterations as slightly to moderate. The severity of alteration of individual fish of treatment 0, 10 and 20% LBC ranged values from 5 to 40 (HAI average of 20.1, 17.5 and 17.6, respectively, P > 0.05), and differs from 30% LBC, that ranged from 6 to 129 (HAI mean of 77.2, P < 0.05). The HAI value in the treatments 0, 10 and 20% LBC reveals gill tissue with injuries classified from slightly to moderate, while in 30% LBC moderate to severe, consequence of the onset of necrosis in the tissue of two fish that compromises the normal functioning of the organ. In relation to frequency of gill alterations, evaluated according to absence of alterations (0) to highly frequent (+++), histological alterations were observed in all evaluated fish, with a trend of higher frequency in 0% LBC. The concentration of Na+, Cl-, K+ and Ca2+ did not changed in all treatments (P > 0.05), indicating similar capacity of ion exchange. The concentrations of bovine colostrum used in diets of present study did not impair the alterations observed in the gills of juvenile pacu.

Keywords: histological alterations of gill tissue, ionic status, lyophilized bovine colostrum, optical microscopy

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87 Indeterminacy: An Urban Design Tool to Measure Resilience to Climate Change, a Caribbean Case Study

Authors: Tapan Kumar Dhar

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How well are our city forms designed to adapt to climate change and its resulting uncertainty? What urban design tools can be used to measure and improve resilience to climate change, and how would they do so? In addressing these questions, this paper considers indeterminacy, a concept originated in the resilience literature, to measure the resilience of built environments. In the realm of urban design, ‘indeterminacy’ can be referred to as built-in design capabilities of an urban system to serve different purposes which are not necessarily predetermined. An urban system, particularly that with a higher degree of indeterminacy, can enable the system to be reorganized and changed to accommodate new or unknown functions while coping with uncertainty over time. Underlying principles of this concept have long been discussed in the urban design and planning literature, including open architecture, landscape urbanism, and flexible housing. This paper argues that the concept indeterminacy holds the potential to reduce the impacts of climate change incrementally and proactively. With regard to sustainable development, both planning and climate change literature highly recommend proactive adaptation as it involves less cost, efforts, and energy than last-minute emergency or reactive actions. Nevertheless, the concept still remains isolated from resilience and climate change adaptation discourses even though the discourses advocate the incremental transformation of a system to cope with climatic uncertainty. This paper considers indeterminacy, as an urban design tool, to measure and increase resilience (and adaptive capacity) of Long Bay’s coastal settlements in Negril, Jamaica. Negril is one of the popular tourism destinations in the Caribbean highly vulnerable to sea-level rise and its associated impacts. This paper employs empirical information obtained from direct observation and informal interviews with local people. While testing the tool, this paper deploys an urban morphology study, which includes land use patterns and the physical characteristics of urban form, including street networks, block patterns, and building footprints. The results reveal that most resorts in Long Bay are designed for pre-determined purposes and offer a little potential to use differently if needed. Additionally, Negril’s street networks are found to be rigid and have limited accessibility to different points of interest. This rigidity can expose the entire infrastructure further to extreme climatic events and also impedes recovery actions after a disaster. However, Long Bay still has room for future resilient developments in other relatively less vulnerable areas. In adapting to climate change, indeterminacy can be reached through design that achieves a balance between the degree of vulnerability and the degree of indeterminacy: the more vulnerable a place is, the more indeterminacy is useful. This paper concludes with a set of urban design typologies to increase the resilience of coastal settlements.

Keywords: climate change adaptation, resilience, sea-level rise, urban form

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86 Co₂Fe LDH on Aromatic Acid Functionalized N Doped Graphene: Hybrid Electrocatalyst for Oxygen Evolution Reaction

Authors: Biswaranjan D. Mohapatra, Ipsha Hota, Swarna P. Mantry, Nibedita Behera, Kumar S. K. Varadwaj

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Designing highly active and low-cost oxygen evolution (2H₂O → 4H⁺ + 4e⁻ + O₂) electrocatalyst is one of the most active areas of advanced energy research. Some precious metal-based electrocatalysts, such as IrO₂ and RuO₂, have shown excellent performance for oxygen evolution reaction (OER); however, they suffer from high-cost and low abundance which limits their applications. Recently, layered double hydroxides (LDHs), composed of layers of divalent and trivalent transition metal cations coordinated to hydroxide anions, have gathered attention as an alternative OER catalyst. However, LDHs are insulators and coupled with carbon materials for the electrocatalytic applications. Graphene covalently doped with nitrogen has been demonstrated to be an excellent electrocatalyst for energy conversion technologies such as; oxygen reduction reaction (ORR), oxygen evolution reaction (OER) & hydrogen evolution reaction (HER). However, they operate at high overpotentials, significantly above the thermodynamic standard potentials. Recently, we reported remarkably enhanced catalytic activity of benzoate or 1-pyrenebutyrate functionalized N-doped graphene towards the ORR in alkaline medium. The molecular and heteroatom co-doping on graphene is expected to tune the electronic structure of graphene. Therefore, an innovative catalyst architecture, in which LDHs are anchored on aromatic acid functionalized ‘N’ doped graphene may presumably boost the OER activity to a new benchmark. Herein, we report fabrication of Co₂Fe-LDH on aromatic acid (AA) functionalized ‘N’ doped reduced graphene oxide (NG) and studied their OER activities in alkaline medium. In the first step, a novel polyol method is applied for synthesis of AA functionalized NG, which is well dispersed in aqueous medium. In the second step, Co₂Fe LDH were grown on AA functionalized NG by co-precipitation method. The hybrid samples are abbreviated as Co₂Fe LDH/AA-NG, where AA is either Benzoic acid or 1, 3-Benzene dicarboxylic acid (BDA) or 1, 3, 5 Benzene tricarboxylic acid (BTA). The crystal structure and morphology of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). These studies confirmed the growth of layered single phase LDH. The electrocatalytic OER activity of these hybrid materials was investigated by rotating disc electrode (RDE) technique on a glassy carbon electrode. The linear sweep voltammetry (LSV) on these catalyst samples were taken at 1600rpm. We observed significant OER performance enhancement in terms of onset potential and current density on Co₂Fe LDH/BTA-NG hybrid, indicating the synergic effect. This exploration of molecular functionalization effect in doped graphene and LDH system may provide an excellent platform for innovative design of OER catalysts.

Keywords: π-π functionalization, layered double hydroxide, oxygen evolution reaction, reduced graphene oxide

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85 Elevated Celiac Antibodies and Abnormal Duodenal Biopsies Associated with IBD Markers: Possible Role of Altered Gut Permeability and Inflammation in Gluten Related Disorders

Authors: Manav Sabharwal, Ruda Rai Md, Candace Parker, James Ridley

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Wheat is one of the most commonly consumed grains worldwide, which contains gluten. Nowadays, gluten intake is considered to be a trigger for GRDs, including Celiac disease (CD), a common genetic disease affecting 1% of the US population, non-celiac gluten sensitivity (NCGS) and wheat allergy. NCGS is being recognized as an acquired gluten-sensitive enteropathy that is prevalent across age, ethnic and geographic groups. The cause of this entity is not fully understood, and recent studies suggest that it is more common in participants with irritable bowel syndrome (IBS), with iron deficiency anemia, symptoms of fatigue, and has considerable overlap in symptoms with IBS and Crohn’s disease. However, these studies were lacking in availability of complete serologies, imaging tests and/or pan-endoscopy. We performed a prospective study of 745 adult patients who presented to an outpatient clinic for evaluation of chronic upper gastro-intestinal symptoms and subsequently underwent an upper endoscopic (EGD) examination as standard of care. Evaluation comprised of comprehensive celiac antibody panel, inflammatory bowel disease (IBD) serologic markers, duodenal biopsies and Small Bowel Video Capsule Endoscopy (VCE), when available. At least 6 biopsy specimens were obtained from the duodenum and proximal jejunum during EGD, and CD3+ Intraepithelial lymphocytes (IELs) and villous architecture were evaluated by a single experienced pathologist, and VCE was performed by a single experienced gastroenterologist. Of the 745 patients undergoing EGD, 12% (93/745) patients showed elevated CD3+ IELs in the duodenal biopsies. 52% (387/745) completed a comprehensive CD panel and 7.2% (28/387) were positive for at least 1 CD antibody (Tissue transglutaminase (tTG), being the most common antibody in 65% (18/28)). Of these patients, 18% (5/28) showed increased duodenal CD3+ IELs, but 0% showed villous blunting or distortion to meet criteria for CD. Surprisingly, 43% (12/28) were positive for at 1 IBD serology (ASCA, ANCA or expanded IBD panel (LabCorp)). Of these 28 patients, 29% (8/28) underwent a SB VCE, of which 100 % (8/8) showed significant jejuno-ileal mucosal lesions diagnostic for IBD. Findings of abnormal CD antibodies (7.2%, 28/387) and increased CD3+ IELs on duodenal biopsy (12%, 93/745) were observed frequently in patients with UGI symptoms undergoing EGD in an outpatient clinic. None met criteria for CD, and a high proportion (43%, 12/28) showed evidence of overlap with IBD. This suggests a potential causal link of acquired GRDs to underlying inflammation and gut mucosal barrier disruption. Further studies to investigate a role for abnormal antigen presentation of dietary gluten to gut associated lymphoid tissue as a cause are justified. This may explain a high prevalence of GRDs in the population and correlation with IBS, IBD and other gut inflammatory disorders.

Keywords: celiac, gluten sensitive enteropathy, lymphocitic enteritis, IBS, IBD

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84 The Home as Memory Palace: Three Case Studies of Artistic Representations of the Relationship between Individual and Collective Memory and the Home

Authors: Laura M. F. Bertens

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The houses we inhabit are important containers of memory. As homes, they take on meaning for those who live inside, and memories of family life become intimately tied up with rooms, windows, and gardens. Each new family creates a new layer of meaning, resulting in a palimpsest of family memory. These houses function quite literally as memory palaces, as a walk through a childhood home will show; each room conjures up images of past events. Over time, these personal memories become woven together with the cultural memory of countries and generations. The importance of the home is a central theme in art, and several contemporary artists have a special interest in the relationship between memory and the home. This paper analyses three case studies in order to get a deeper understanding of the ways in which the home functions and feels like a memory palace, both on an individual and on a collective, cultural level. Close reading of the artworks is performed on the theoretical intersection between Art History and Cultural Memory Studies. The first case study concerns works from the exhibition Mnemosyne by the artist duo Anne and Patrick Poirier. These works combine interests in architecture, archaeology, and psychology. Models of cities and fantastical architectural designs resemble physical structures (such as the brain), architectural metaphors used in representing the concept of memory (such as the memory palace), and archaeological remains, essential to our shared cultural memories. Secondly, works by Do Ho Suh will help us understand the relationship between the home and memory on a far more personal level; outlines of rooms from his former homes, made of colourful, transparent fabric and combined into new structures, provide an insight into the way these spaces retain individual memories. The spaces have been emptied out, and only the husks remain. Although the remnants of walls, light switches, doors, electricity outlets, etc. are standard, mass-produced elements found in many homes and devoid of inherent meaning, together they remind us of the emotional significance attached to the muscle memory of spaces we once inhabited. The third case study concerns an exhibition in a house put up for sale on the Dutch real estate website Funda. The house was built in 1933 by a Jewish family fleeing from Germany, and the father and son were later deported and killed. The artists Anne van As and CA Wertheim have used the history and memories of the house as a starting point for an exhibition called (T)huis, a combination of the Dutch words for home and house. This case study illustrates the way houses become containers of memories; each new family ‘resets’ the meaning of a house, but traces of earlier memories remain. The exhibition allows us to explore the transition of individual memories into shared cultural memory, in this case of WWII. Taken together, the analyses provide a deeper understanding of different facets of the relationship between the home and memory, both individual and collective, and the ways in which art can represent these.

Keywords: Anne and Patrick Poirier, cultural memory, Do Ho Suh, home, memory palace

Procedia PDF Downloads 159
83 Socio-Economic Transformation of Barpak Post-Earthquake Reconstruction

Authors: Sudikshya Bhandari, Jonathan K. London

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The earthquake of April 2015 was one of the biggest disasters in the history of Nepal. The epicenter was located near Barpak, north of the Gorkha district. Before the disaster, this settlement was a compact and homogeneous settlement manifesting its uniqueness through the social and cultural activities, and a distinct vernacular architecture. Narrow alleys with stone paved streets, buildings with slate roofs, and common spaces between the houses made this settlement socially, culturally, and environmentally cohesive. With the presence of micro hydro power plants, local economic activities enabled the local community to exist and thrive. Agriculture and animal rearing are the sources of livelihood for the majority of families, along with the booming homestays (where local people welcome guests to their home, as a business) and local shops. Most of these activities are difficult to find as the houses have been destroyed with the earthquake and the process of reconstruction has been transforming the outlook of the settlement. This study characterized the drastic transformation in Barpak post-earthquake, and analyzed the consequences of the reconstruction process. In addition, it contributes to comprehending a broader representation about unsustainability created by the lack of contextual post-disaster development. Since the research is based in a specific area, a case study approach was used. Sample houses were selected on the basis of ethnicity and house typology. Mixed methods such as key informant and semi structured interviews, focus groups, observations and photographs are used for the collection of data. The research focus is predominantly on the physical change of the house typology from vernacular to externally adopted designs. This transformation of the house entails socio-cultural changes such as social fragmentation with differences among the rich and the poor and decreases in the social connectivity within families and neighborhood. Families have found that new houses require more maintenance and resources that have increased their economic expenses. The study also found that the reconstructed houses are not thermally comfortable in the cold climate of Barpak, leading to the increased use of different sources of heating like electric heaters and more firewood. Lack of storage spaces for crops and livestock have discouraged them to pursue traditional means of livelihood and depend more on buying food from stores, ultimately making it less economical for most of the families. The transformation of space leading to the economic, social and cultural changes demonstrates the unsustainability of Barpak. Conclusions from the study suggest place based and inclusive planning and policy formations that include locals as partners, identifying the possible ways to minimize the impact and implement these recommendations into the future policy and planning scenarios.

Keywords: earthquake, Nepal, reconstruction, settlement, transformation

Procedia PDF Downloads 118
82 Environmental Impact of a New-Build Educational Building in England: Life-Cycle Assessment as a Method to Calculate Whole Life Carbon Emissions

Authors: Monkiz Khasreen

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In the context of the global trend towards reducing new buildings carbon footprint, the design team is required to make early decisions that have a major influence on embodied and operational carbon. Sustainability strategies should be clear during early stages of building design process, as changes made later can be extremely costly. Life-Cycle Assessment (LCA) could be used as the vehicle to carry other tools and processes towards achieving the requested improvement. Although LCA is the ‘golden standard’ to evaluate buildings from 'cradle to grave', lack of details available on the concept design makes LCA very difficult, if not impossible, to be used as an estimation tool at early stages. Issues related to transparency and accessibility of information in the building industry are affecting the credibility of LCA studies. A verified database derived from LCA case studies is required to be accessible to researchers, design professionals, and decision makers in order to offer guidance on specific areas of significant impact. This database could be the build-up of data from multiple sources within a pool of research held in this context. One of the most important factors that affects the reliability of such data is the temporal factor as building materials, components, and systems are rapidly changing with the advancement of technology making production more efficient and less environmentally harmful. Recent LCA studies on different building functions, types, and structures are always needed to update databases derived from research and to form case bases for comparison studies. There is also a need to make these studies transparent and accessible to designers. The work in this paper sets out to address this need. This paper also presents life-cycle case study of a new-build educational building in England. The building utilised very current construction methods and technologies and is rated as BREEAM excellent. Carbon emissions of different life-cycle stages and different building materials and components were modelled. Scenario and sensitivity analyses were used to estimate the future of new educational buildings in England. The study attempts to form an indicator during the early design stages of similar buildings. Carbon dioxide emissions of this case study building, when normalised according to floor area, lie towards the lower end of the range of worldwide data reported in the literature. Sensitivity analysis shows that life cycle assessment results are highly sensitive to future assumptions made at the design stage, such as future changes in electricity generation structure over time, refurbishment processes and recycling. The analyses also prove that large savings in carbon dioxide emissions can result from very small changes at the design stage.

Keywords: architecture, building, carbon dioxide, construction, educational buildings, England, environmental impact, life-cycle assessment

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81 Examination of Indoor Air Quality of Naturally Ventilated Dwellings During Winters in Mega-City Kolkata

Authors: Tanya Kaur Bedi, Shankha Pratim Bhattacharya

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The US Environmental Protection Agency defines indoor air quality as “The air quality within and around buildings, especially as it relates to the health and comfort of building occupants”. According to the 2021 report by the Energy Policy Institute at Chicago, Indian residents, a country which is home to the highest levels of air pollution in the world, lose about 5.9 years from life expectancy due to poor air quality and yet has numerous dwellings dependent on natural ventilation. Currently the urban population spends 90% of the time indoors, this scenario raises a concern for occupant health and well-being. The built environment can affect health directly and indirectly through immediate or long-term exposure to indoor air pollutants. Health effects associated with indoor air pollutants include eye/nose/throat irritation, respiratory diseases, heart disease, and even cancer. This study attempts to demonstrate the causal relationship between the indoor air quality and its determining aspects. Detailed indoor air quality audits were conducted in residential buildings located in Kolkata, India in the months of December and January 2021. According to the air pollution knowledge assessment city program in India, Kolkata is also the second most polluted mega-city after Delhi. Although the air pollution levels are alarming year-long, the winter months are most crucial due to the unfavorable environmental conditions. While emissions remain typically constant throughout the year, cold air is denser and moves slower than warm air, trapping the pollution in place for much longer and consequently is breathed in at a higher rate than the summers. The air pollution monitoring period was selected considering environmental factors and major pollution contributors like traffic and road dust. This study focuses on the relationship between the built environment and the spatial-temporal distribution of air pollutants in and around it. The measured parameters include, temperature, relative humidity, air velocity, particulate matter, volatile organic compounds, formaldehyde, and benzene. A total of 56 rooms were audited, selectively targeting the most dominant middle-income group. The data-collection was conducted using a set of instruments positioned in the human breathing-zone. The study assesses indoor air quality based on factors determining natural ventilation and air pollution dispersion such as surrounding environment, dominant wind, openable window to floor area ratio, windward or leeward side openings, and natural ventilation type in the room: single side or cross-ventilation, floor height, residents cleaning habits, etc.

Keywords: indoor air quality, occupant health, urban housing, air pollution, natural ventilation, architecture, urban issues

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80 Identifying Confirmed Resemblances in Problem-Solving Engineering, Both in the Past and Present

Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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79 Development of a Human Skin Explant Model for Drug Metabolism and Toxicity Studies

Authors: K. K. Balavenkatraman, B. Bertschi, K. Bigot, A. Grevot, A. Doelemeyer, S. D. Chibout, A. Wolf, F. Pognan, N. Manevski, O. Kretz, P. Swart, K. Litherland, J. Ashton-Chess, B. Ling, R. Wettstein, D. J. Schaefer

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Skin toxicity is poorly detected during preclinical studies, and drug-induced side effects in humans such as rashes, hyperplasia or more serious events like bullous pemphigus or toxic epidermal necrolysis represent an important hurdle for clinical development. In vitro keratinocyte-based epidermal skin models are suitable for the detection of chemical-induced irritancy, but do not recapitulate the biological complexity of full skin and fail to detect potential serious side-effects. Normal healthy skin explants may represent a valuable complementary tool, having the advantage of retaining the full skin architecture and the resident immune cell diversity. This study investigated several conditions for the maintenance of good morphological structure after several days of culture and the retention of phase II metabolism for 24 hours in skin explants in vitro. Human skin samples were collected with informed consent from patients undergoing plastic surgery and immediately transferred and processed in our laboratory by removing the underlying dermal fat. Punch biopsies of 4 mm diameter were cultured in an air-liquid interface using transwell filters. Different cultural conditions such as the effect of calcium, temperature and cultivation media were tested for a period of 14 days and explants were histologically examined after Hematoxylin and Eosin staining. Our results demonstrated that the use of Williams E Medium at 32°C maintained the physiological integrity of the skin for approximately one week. Upon prolonged incubation, the upper layers of the epidermis become thickened and some dead cells are present. Interestingly, these effects were prevented by addition of EGFR inhibitors such as Afatinib or Erlotinib. Phase II metabolism of the skin such as glucuronidation (4-methyl umbeliferone), sulfation (minoxidil), N-acetyltransferase (p-toluidene), catechol methylation (2,3-dehydroxy naphthalene), and glutathione conjugation (chlorodinitro benzene) were analyzed by using LCMS. Our results demonstrated that the human skin explants possess metabolic activity for a period of at least 24 hours for all the substrates tested. A time course for glucuronidation with 4-methyl umbeliferone was performed and a linear correlation was obtained over a period of 24 hours. Longer-term culture studies will indicate the possible evolution of such metabolic activities. In summary, these results demonstrate that human skin explants maintain a normal structure for several days in vitro and are metabolically active for at least the first 24 hours. Hence, with further characterisation, this model may be suitable for the study of drug-induced toxicity.

Keywords: human skin explant, phase II metabolism, epidermal growth factor receptor, toxicity

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78 Engineering Topology of Photonic Systems for Sustainable Molecular Structure: Autopoiesis Systems

Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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77 Multimodal Biometric Cryptography Based Authentication in Cloud Environment to Enhance Information Security

Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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76 Ensuring Safety in Fire Evacuation by Facilitating Way-Finding in Complex Buildings

Authors: Atefeh Omidkhah, Mohammadreza Bemanian

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The issue of way-finding earmarks a wide range of literature in architecture and despite the 50 year background of way-finding studies, it still lacks a comprehensive theory for indoor settings. Way-finding has a notable role in emergency evacuation as well. People in the panic situation of a fire emergency need to find the safe egress route correctly and in as minimum time as possible. In this regard the parameters of an appropriate way-finding are mentioned in the evacuation related researches albeit scattered. This study reviews the fire safety related literature to extract a way-finding related framework for architectural purposes of the design of a safe evacuation route. In this regard a research trend review in addition with applied methodological approaches review is conducted. Then by analyzing eight original researches related to way-finding parameters in fire evacuation, main parameters that affect way-finding in emergency situation of a fire incident are extracted and a framework was developed based on them. Results show that the issues related to exit route and emergency evacuation can be chased in task oriented studies of way-finding. This research trend aims to access a high-level framework and in the best condition a theory that has an explanatory capability to define differences in way-finding in indoor/outdoor settings, complex/simple buildings and different building types or transitional spaces. The methodological advances demonstrate the evacuation way-finding researches in line with three approaches that the latter one is the most up-to-date and precise method to research this subject: real actors and hypothetical stimuli as in evacuation experiments, hypothetical actors and stimuli as in agent-based simulations and real actors and semi-real stimuli as in virtual reality environment by adding multi-sensory simulation. Findings on data-mining of 8 sample of original researches in way-finding in evacuation indicate that emergency way-finding design of a building should consider two level of space cognition problems in the time of emergency and performance consequences of them in the built environment. So four major classes of problems in way-finding which are visual information deficiency, confusing layout configuration, improper navigating signage and demographic issues had been defined and discussed as the main parameters that should be provided with solutions in design and interior of a building. In the design phase of complex buildings, which face more reported problem in way-finding, it is important to consider the interior components regarding to the building type of occupancy and behavior of its occupants and determine components that tend to become landmarks and set the architectural features of egress route in line with the directions that they navigate people. Research on topological cognition of environmental and its effect on way-finding task in emergency evacuation is proposed for future.

Keywords: architectural design, egress route, way-finding, fire safety, evacuation

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75 Flux-Gate vs. Anisotropic Magneto Resistance Magnetic Sensors Characteristics in Closed-Loop Operation

Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

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The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

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74 Decorative Plant Motifs in Traditional Art and Craft Practices: Pedagogical Perspectives

Authors: Geetanjali Sachdev

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This paper explores the decorative uses of plant motifs and symbols in traditional Indian art and craft practices in order to assess their pedagogical significance within the context of plant study in higher education in art and design. It examines existing scholarship on decoration and plants in Indian art and craft practices. The impulse to elaborate upon an existing form or surface is an intrinsic part of many Indian traditional art and craft traditions where a deeply ingrained love for decoration exists. Indian craftsmen use an array of motifs and embellishments to adorn surfaces across a range of practices, and decoration is widely seen in textiles, jewellery, temple sculptures, vehicular art, architecture, and various other art, craft, and design traditions. Ornamentation in Indian cultural traditions has been attributed to religious and spiritual influences in the lives of India’s art and craft practitioners. Through adornment, surfaces and objects were ritually transformed to function both spiritually and physically. Decorative formations facilitate spiritual development and attune our minds to concepts that support contemplation. Within practices of ornamentation and adornment, there is extensive use of botanical motifs as Indian art and craft practitioners have historically been drawn towards nature as a source of inspiration. This is due to the centrality of agriculture in the lives of Indian people as well as in religion, where plants play a key role in religious rituals and festivals. Plant representations thus abound in two-dimensional and three-dimensional surface designs and patterns where the motifs range from being realistic, highly stylized, and curvilinear forms to geometric and abstract symbols. Existing scholarship reveals that these botanical embellishments reference a wide range of plants that include native and non-indigenous plants, as well as imaginary and mythical plants. Structural components of plant anatomy, such as leaves, stems, branches and buds, and flowers, are part of the repertoire of design motifs used, as are plant forms indicating different stages of growth, such as flowering buds and flowers in full bloom. Symmetry is a characteristic feature, and within the decorative register of various practices, plants are part of border zones and bands, connecting corners and all-over patterns, used as singular motifs and floral sprays on panels, and as elements within ornamental scenes. The results of the research indicate that decoration as a mode of inquiry into plants can serve as a platform to learn about local and global biodiversity and plant anatomy and develop artistic modes of thinking symbolically, metaphorically, imaginatively, and relationally about the plant world. The conclusion is drawn that engaging with ornamental modes of plant representation in traditional Indian art and craft practices is pedagogically significant for two reasons. Decoration as a mode of engagement cultivates both botanical and artistic understandings of plants. It also links learners with the indigenous art and craft traditions of their own culture.

Keywords: art and design pedagogy, decoration, plant motifs, traditional art and craft

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73 Multi-Agent System Based Distributed Voltage Control in Distribution Systems

Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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72 Reliability and Availability Analysis of Satellite Data Reception System using Reliability Modeling

Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

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System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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71 An Adiabatic Quantum Optimization Approach for the Mixed Integer Nonlinear Programming Problem

Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

Abstract:

We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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70 Use of Artificial Neural Networks to Estimate Evapotranspiration for Efficient Irrigation Management

Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

Abstract:

This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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69 Bio-Functionalized Silk Nanofibers for Peripheral Nerve Regeneration

Authors: Kayla Belanger, Pascale Vigneron, Guy Schlatter, Bernard Devauchelle, Christophe Egles

Abstract:

A severe injury to a peripheral nerve leads to its degeneration and the loss of sensory and motor function. To this day, there still lacks a more effective alternative to the autograft which has long been considered the gold standard for nerve repair. In order to overcome the numerous drawbacks of the autograft, tissue engineered biomaterials may be effective alternatives. Silk fibroin is a favorable biomaterial due to its many advantageous properties such as its biocompatibility, its biodegradability, and its robust mechanical properties. In this study, bio-mimicking multi-channeled nerve guidance conduits made of aligned nanofibers achieved by electrospinning were functionalized with signaling biomolecules and were tested in vitro and in vivo for nerve regeneration support. Silk fibroin (SF) extracted directly from silkworm cocoons was put in solution at a concentration of 10wt%. Poly(ethylene oxide) (PEO) was added to the resulting SF solution to increase solution viscosity and the following three electrospinning solutions were made: (1) SF/PEO solution, (2) SF/PEO solution with nerve growth factor and ciliary neurotrophic factor, and (3) SF/PEO solution with nerve growth factor and neurotrophin-3. Each of these solutions was electrospun into a multi-layer architecture to obtain mechanically optimized aligned nanofibrous mats. For in vitro studies, aligned fibers were treated to induce β-sheet formation and thoroughly rinsed to eliminate presence of PEO. Each material was tested using rat embryo neuron cultures to evaluate neurite extension and the interaction with bio-functionalized or non-functionalized aligned fibers. For in vivo studies, the mats were rolled into 5mm long multi-, micro-channeled conduits then treated and thoroughly rinsed. The conduits were each subsequently implanted between a severed rat sciatic nerve. The effectiveness of nerve repair over a period of 8 months was extensively evaluated by cross-referencing electrophysiological, histological, and movement analysis results to comprehensively evaluate the progression of nerve repair. In vitro results show a more favorable interaction between growing neurons and bio-functionalized silk fibers compared to pure silk fibers. Neurites can also be seen having extended unidirectionally along the alignment of the nanofibers which confirms a guidance factor for the electrospun material. The in vivo study has produced positive results for the regeneration of the sciatic nerve over the length of the study, showing contrasts between the bio-functionalized material and the non-functionalized material along with comparisons to the experimental control. Nerve regeneration has been evaluated not only by histological analysis, but also by electrophysiological assessment and motion analysis of two separate natural movements. By studying these three components in parallel, the most comprehensive evaluation of nerve repair for the conduit designs can be made which can, therefore, more accurately depict their overall effectiveness. This work was supported by La Région Picardie and FEDER.

Keywords: electrospinning, nerve guidance conduit, peripheral nerve regeneration, silk fibroin

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68 Deep Learning Framework for Predicting Bus Travel Times with Multiple Bus Routes: A Single-Step Multi-Station Forecasting Approach

Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

Abstract:

Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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67 Segmentation along the Strike-slip Fault System of the Chotts Belt, Southern Tunisia

Authors: Abdelkader Soumaya, Aymen Arfaoui, Noureddine Ben Ayed, Ali Kadri

Abstract:

The Chotts belt represents the southernmost folded structure in the Tunisian Atlas domain. It is dominated by inherited deep extensional E-W trending fault zones, which are reactivated as strike-slip faults during the Cenozoic compression. By examining the geological maps at different scales and based on the fieldwork data, we propose new structural interpretations for the geometries and fault kinematics in the Chotts chain. A set of ENE-WSW right-lateral en echelon folds, with curved shapes and steeply inclined southern limbs, is visible in the map view of this belt. These asymmetric tight anticlines are affected by E-W trending fault segments linked by local bends and stepovers. The revealed kinematic indicators along one of these E-W striated faults (Tafferna segment), such as breccias and gently inclined slickenlines (N094, 80N, 15°W pitch angles), show direct evidence of dextral strike-slip movement. The calculated stress tensors from corresponding faults slip data reveal an overall strike-slip tectonic regime with reverse component and NW-trending sub-horizontal σ1 axis ranking between N130 to N150. From west to east, we distinguished several types of structures along the segmented dextral fault system of the Chotts Range. The NE-SW striking fold-thrust belt (~25 km-long) between two continuously linked E-W fault segments (NW of Tozeur town) has been suggested as a local restraining bend. The central part of the Chotts chain is occupied by the ENE-striking Ksar Asker anticlines (Taferna, Torrich, and Sif Laham), which are truncated by a set of E-W strike-slip fault segments. Further east, the fault segments of Hachichina and Sif Laham connected across the NW-verging asymmetric fold-thrust system of Bir Oum Ali, which can be interpreted as a left-stepping contractional bend (~20 km-long). The oriental part of the Chotts belt corresponds to an array of subparallel E-W oriented fault segments (i.e., Beidha, Bouloufa, El Haidoudi-Zemlet El Beidha) with similar lengths (around 10 km). Each of these individual separated segments is associated with curved ENE-trending en echelon right-stepping anticlines. These folds are affected by a set of conjugate R and R′ shear-type faults indicating a dextral strike-lip motion. In addition, the relay zones between these E-W overstepping fault segments define local releasing stepovers dominated by NW-SE subsidiary faults. Finally, the Chotts chain provides well-exposed examples of strike-slip tectonics along E-W distributed fault segments. Each fault zone shows a typical strike-slip architecture, including parallel fault segments connecting via local stepovers or bends. Our new structural interpretations for this region reveal a great influence of the E-W deep fault segments on regional tectonic deformations and stress field during the Cenozoic shortening.

Keywords: chotts belt, tunisian atlas, strike-slip fault, stepovers, fault segments

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